In neurodegeneration, the progressive loss of structure or function of neurons in the brain, there are many types of degeneration in brain white matter (“WM”). Two major types of degeneration include myelin degradation (e.g., demyelination and dysmyelination) and axonal loss, both of which are hallmarks of neurodegenerative diseases. In lay terms, myelin degradation can be characterized as a reduction of the thickness of the myelin sheath (a coaxial coating of an axon consisting of multiple lipid layers). Axonal loss can be characterized as the removal of an axon altogether, causing fluid to be substituted in its place. Axonal loss is considered to be the histological substrate for permanent disability, while myelin degradation, unlike axonal loss, can be reversible. Currently, however, there is no known noninvasive method for differentiating between axonal loss and myelin degradation.
Axonal loss and myelin degradation myelin degradation both include subtle microstructural changes affecting tissue microarchitecture at a micrometer length scale (e.g., a length scale of about 1000 times below the nominal resolution in millimeters of magnetic resonance imaging (“MRI”) scanners). However, MRI is currently the only practically viable noninvasive probe for soft tissues. Thus, these subtle changes from axonal loss and myelin degradation myelin degradation can be well below the nominal spatial resolution that could ever be achieved in the foreseeable future, which presents a significant challenge to distinguish between, and to quantify the degree (e.g., relative to age-matched normal controls) of, both of these pathological processes.
Thus, it may be beneficial to provide non-invasive systems, methods and computer-accessible mediums that can differentiate between the two processes, and can quantify the degree of either pathological processes. Such systems, methods and computer-accessible mediums would be of significant clinical value for myelin related disorders (e.g., multiple sclerosis, leukodystrophy etc.) neurodegenerative disorders (e.g., Alzheimer's disease, Parkinson's disease, Huntington's disease, amyotrophic lateral sclerosis, traumatic etc.), as well as for neuropsychiatric disorders (e.g. schizophrenia), neurodevelopmental disorders (e.g. autism, attention deficit hyperactivity disorder) and other disorders. Such exemplary systems, methods and computer-accessible medium could be valuable both for diagnostic purposes (e.g., for early detection), as well as for quantitative assessment of the efficacy of treatment options.